Evolution in technology has made possible more and more complex electronic and electro-mechanical systems. Large-scale systems may typically be found in such fields as radar, sonar, cable television, broadcasting, television, air traffic control, and satellite communications systems, to name a few. Currently most organizations that own such large scale electronic systems (e.g., the Federal Aviation Administration (FAA), the Federal Communications Commission (FCC), United States Navy (USN), United States Air Force (USAF), United States Marine Corps (USMC), United States Coast Guard (USCG), and United States Army (USA) utilize general purpose test equipment to maintain and repair their systems. Such general purpose test equipment usually consists of single-purpose instruments like oscilloscopes, spectrum analyzers, digital multimeters, logic analyzers, and network analyzers, etc. Technicians typically require weeks of training to acquire sufficient knowledge to operate these various instruments and to properly interpret test results obtained therefrom. Further, such test instruments, for the most part, have no method of storing and recalling the results from previous tests. Therefore, there is an inherent reliance on the technician's experience and memory to understand current test results in a historical context.
In addition, preparing such general purpose test equipment to perform a given measurement requires setting numerous controls to their correct values/positions so that test results may be viewed and interpreted correctly. Technicians are most familiar and experienced with test instruments that they use on a routine basis. Test instruments that they use infrequently are often, coincidentally, more difficult to operate, which results because such instruments typically require a greater degree of interpretation by the technician. In addition, the use and set-up of test instruments is rarely a primary training objective in operation and maintenance schools for complex electronic systems. Consequently, in typical training courses, the test instruments are only covered in enough detail to support basic tests on the system being taught or under test. There appears to be an inverse relationship between the amount of training received and the proficiency required to use many of the more complex test instruments, for example, spectrum analyzers and oscilloscopes. In the long run, this tends to introduce two types of errors into the test process, which affect the quality of the maintenance performed on the system under test. The two types of errors are: errors attributed to incorrect setup of the test instrument itself, and errors attributed to incorrect interpretation of the results from the test instrument. These shortcomings can be significantly reduced or eliminated through the introduction of standardized testing processes and test equipment for complex systems.
The majority of current testing technologies rely on human experience and interpretation to derive test results. While oscilloscopes are excellent devices to display waveform characteristics, specifically period (time), voltage, and wave shape, they rely on visual interpretation by their user to achieve a result. Spectrum and network analyzers provide data that is filtered through fast Fourier transforms (FFTs) and differential equations before display. As with oscilloscopes, the results of FFTs require visual interpretation for analysis.
In the case of an oscilloscope, there is only simple conversion from an electronic signal to a visual representation thereof involved. With spectrum analyzers, there is a conversion and derivation of a group of signals required to develop a visual representation. In other words, the displayed result of a spectrum analyzer or the like is not easily manually linked to one or more input signals.
An instrument that could convert such input signals to digital form, and normalize the signals could provide more consistent analysis and remove a technician's perception errors from the test results. Such an instrument could significantly narrow the kinds, frequency, and degree of errors made by the technician, thereby improving the measurement process by reducing operator error. Such an approach is used in the system and method of the present invention.
Another shortcoming of prior art instruments is that specialized test instruments rarely, if ever, can recall measurements taken at a given test point for comparison with a current measurement. The lack of this ability in current maintenance practices on complex systems demands additional effort on the part of the technician, reduces the availability of the system under test, and increases the overall cost of system ownership. It is estimated that the cost of technical training of maintenance personnel contributes approximately 20% or more to the cost of the employee. It is also estimated that training costs are likely to continue to increase with the increasing complexity of systems requiring maintenance.
The majority of advanced technical schools are designed to familiarize the technician with operational aspects, components, data flow, signal paths, and the capabilities of the system upon which they are being trained. The knowledge gained in training programs at such training schools is volatile and, when not in use, tends to degrade and quickly dissipate. This in turn requires recurrent and expensive retraining or on-the-job training of technicians, which, in turn, limits the availability of both the system under test and the technician while that retraining takes place.
The reference materials for large scale systems are typically technical manuals developed explicitly for each system. These manuals are usually the basis for the training curricula for the system courses including any computer-based training. The manuals, in hard copy form, may be thousands of pages long and include thousands of diagrams. Finding the necessary text and/or diagram(s) pertinent to a particular maintenance or troubleshooting task may be time consuming if not almost impossible. The search process may break the technician's train of thought as well as consume valuable time. Even when the manuals are available in digital form, their lack of integration with the test environment still slows the technician in the performance of his or her duties.
The system and method of the present invention, on the other hand, integrates necessary technical manuals into the test environment, thereby significantly reducing the technician's loss of focus on the system under test. This lowers the amount of time spent acclimating the technician to a specific area or component of the system. Additionally, using relational database techniques, the interactive help feature of the present invention is synchronized with the component that is being tested and analyzed. In other words, the technician saves time in locating the correct text or diagram in the manuals as the inventive system automatically locates such text or diagram depending on the particular component, sub-assembly, area, etc. of the system being tested.
Owners of complex systems, for example, the aforementioned organizations, generally maintain large and expensive technical support staffs for those systems. These technical support staffs are either deployed on-site or remotely from the systems. Typically, the remote support staffs have the more expert technicians who may, for example, have access directly to technical support personnel at the manufacturer of the system being maintained. Communication between the remote and the on-site support personnel is normally accomplished by email, video conference, and voice communication. Unfortunately, today's test equipment generally does not support interactive technical support. The goal of the many organizations owning complex systems is to reduce the number of on-site technical support personnel. This goal places greater demands on fewer personnel and increases reliance on the remote support staff to reduce on-site expert visits. The system of the present invention integrates interactive remote support capability by, for example, applying recent personal computing and communications advances to support near real-time technical interactivity. The use of the inventive system, therefore, has a significant positive effect on the required number of on-site technical support occurrences, the amount of system downtime, and duration of the downtime incidents.
While innovative analytical techniques have been employed in mechanical systems to identify and predict failure modes, rates, and frequencies, these techniques have heretofore not often been applied to many complex electronic systems. Many software techniques that have previously been applied to spatial and pattern recognition systems may, however, also be applied to electronic waveforms and signals. Until recently, one problem with applying such techniques to the analysis of waveforms in the maintenance environment has been the lack of the necessary computer processing power required to support such analysis. The test system of the present invention uses such techniques because microprocessors are currently available which provide such processing capability. Advances in processor capabilities, software, and database technologies all present an opportunity to apply adaptive logic, heuristic, or neural network models that can run on microprocessors such as those found in personal computer class machines. These advances also provide the capability to adapt complex models that can replicate a complex system under test with a far greater degree of accuracy and detail than has heretofore been possible. Such modeling is also provided in the system of the present invention.